- 1CIMA Research Foundation, Wildfire Unit, via A. Magliotto 2, 17100 Savona, Italy (andrea.trucchia@cimafoundation.org)
- 2Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, via All’Opera Pia, 13, Genova, 16145, Italy
- 3Dipartimento della Protezione Civile, Presidenza del Consiglio dei Ministri, via Vitorchiano, 2, Roma, 00189, Italy
Changes in wildfire regimes observed globally due to land use transformation, human activity and climate change are compelling the development of Forest Fire Danger Rating systems capable of accurately identifying spatio-temporal patterns of increased fire danger for effective wildfire risk management, with a focus on distinguishing extreme dangerous conditions for a proper resources deployment.
Many existing models primarily rely on weather conditions, often overlooking critical factors such as fuel and topography, which significantly influence wildfire behavior. However, these characteristics play a crucial role in wildfire activity by identifying areas where their interaction with fire-prone weather can result in extreme behaviors, leading to the majority of fire-related damage and civil protection emergencies.
This study analyzes RISICO, a fire danger rating system that explicitly incorporates fuel and other geo-environmental characteristics of the territory into its computations. Developed in the early 2000s for Italy, RISICO has been operationally used by the Italian Civil Protection system for decades, supporting the issuing of the National forest fires risk bulletin. The latest version of the model further enhances the integration of fuel in its calculations.
The model's performance has been evaluated over the past fifteen years of wildfire data in Italy, alongside other fire danger indices from the literature. The discrimination and detection capabilities of the indices have been assessed, along with their reliability, to ensure their suitability for operational use.
RISICO demonstrates strong performance in identifying wildfire-related conditions while reducing the extent of areas classified as high danger, thereby improving its applicability for efficient wildfire risk management. This study highlights the importance of incorporating fuel and other geo-environmental characteristics into fire danger models, moving beyond sole reliance on fire weather assessments, and enhancing their operational effectiveness in wildfire risk management practices.
Keywords: wildfire danger, wildfire risk management, fire weather
How to cite: Perello, N., Trucchia, A., Meschi, G., Ghasemiazma, F., D'Andrea, M., Degli Esposti, S., Fiorucci, P., Gollini, A., and Negro, D.: Fuel-aware Forest Fire Danger Rating System RISICO: a comparative study for Italy , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6955, https://doi.org/10.5194/egusphere-egu25-6955, 2025.
